Search guided by location and context

ABSTRACT

The subject disclosure pertains to web searches and more particularly toward influencing resultant content to increase relevancy. The resultant content can be influenced by reconfiguring a query and/or filtering results based on user location and/or context information (e.g., user characteristics/profile, prior interaction/usage temporal, current events, and third party state/context . . . ). Furthermore, the disclosure provides for query execution on at least a subset of designated web content, for example as specified by a user. Still further yet, a localized marketing system is disclosed that provides discount offers to users that match merchant criteria including proximity. A system for actively probing populations of users with different parameters and monitoring responses can be employed to collect data for identifying the best discounts and deadlines to offer to users to achieve desired results.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to U.S. application Ser. No. 11/427,296,filed Jun. 28, 2006, entitled “SEARCH OVER DESIGNATED CONTENT,” and U.S.application Ser. No. 11/427,290, filed Jun. 28, 2006 entitled “LOCALIZEDMARKETING.” The entireties of these applications are incorporated hereinby reference.

BACKGROUND

The Internet and World Wide Web continue to expand rapidly with respectto both volume of information and number of users. The Internet is acollection of interconnected computer networks. The World Wide Web, orsimply the web, is a service that connects numerous Internet accessiblesites via hyperlinks and uniform resource locators (URLs). As a whole,the web provides a global space for accumulation, exchange, anddissemination of all types of information. For instance, information canbe provided by way of online newspapers, magazines, advertisements,books, pictures, audio, video and the like. The increase in usage islargely driven by the increase in available information pertinent touser needs. By way of example, the web and Internet was initiallyutilized solely by researches to exchange information. At present,people of all occupations and lifestyles utilize the web to manage theirbank accounts, complete their taxes, view product information, sell andpurchase products, download music, take classes, research topics, andfind directions, among other things. Further, usage will continue toflourish as additional relevant information becomes available over theweb.

To maximize the likelihood of locating relevant information amongst anabundance of data, search engines are often employed over the web or asubset of pages thereof. In some instances, a user is aware of the name,server or URL associated with the site that the user desires to access.In such situations, the user can access the site by simply entering theURL in an address bar of a browser and connecting to the site. However,in most instances, the user does not know the URL or name of the sitethat includes the desired information. To locate a site or correspondingURL of interest, users often employ a search engine to facilitatelocating and accessing sites based on keywords and operators.

A web search engine, or simply a search engine, is a tool thatfacilitates web navigation based on entry of a search query comprisingone or more keywords. Upon receipt of a query, the search engineretrieves a list of websites, typically ranked based on relevance to thequery. To enable this functionality, the search engine must generate andmaintain a supporting infrastructure.

Search engine agents, often referred to as spiders or crawlers, navigatewebsites in a methodical manner and retrieve information about sitesvisited. For example, a crawler can make a copy of all or a portion ofwebsites and related information. The search engine subsequentlyanalyzes the content captured by one or more crawlers to determine how apage will be indexed. Indexing transforms website data into a form, theindex, which can be employed at search time to facilitate identificationof content. Some engines will index all words on a website while othersmay in only index terms associated with particular tags (e.g., title,header or meta-tag). Crawlers must also periodically revisit web pagesto detect and capture changes thereto since the last indexing.

Upon entry of one or more keywords as a search query, the search engineretrieves information that matches the query from the index, ranks thesites that match the query, generates a snippet of text associated withmatching sites and displays the results to a user. Furthermore,advertisements relating to the search terms can also be displayedtogether with the results. The user can thereafter scroll through aplurality of returned sites, ads and the like in an attempt to identifyinformation of interest. However, this can be an extremelytime-consuming and frustrating process as search engines can return asubstantial number of sites. More often than not, the user is forced tonarrow the search iteratively by altering and/or adding keywords andoperators to obtain the identity of websites including relevantinformation.

SUMMARY

The following presents a simplified summary in order to provide a basicunderstanding of some aspects of the claimed subject matter. Thissummary is not an extensive overview. It is not intended to identifykey/critical elements or to delineate the scope of the claimed subjectmatter. Its sole purpose is to present some concepts in a simplifiedform as a prelude to the more detailed description that is presentedlater.

Briefly described, the subject innovation pertains to location and/orcontext based search. Given the ever-increasing amount of informationavailable on the web and how the size of this information in totaloutpaces display real estate, bandwidth, memory and processingcapabilities, the need for relevant information becomes more critical.According to an aspect of the subject innovation, returned web content(e.g., results, advertisements . . . ) can be limited, filtered orconstrained to data that is either or both of near and relevant. Morespecifically, a search engine can interact with a location component toreceive a location of a user, or alternatively a location of interest,and utilize this information to affect the resulting web content.Additionally or alternatively, context information including but notlimited to user, temporal, current events and third party context can beutilized to identify relevant content.

In accordance with another aspect of the subject innovation, a websearch can be evaluated with respect to designated content. Rather thanevaluating a query with respect all web content located by crawlers,select web content can be specified by a user or otherwise determined orinferred. In this manner, results can be delivered that are most likelyto include information a user desires. Furthermore, the query can beevaluated with respect to content that may not have been identified bysearch engine crawlers.

According to yet another aspect, a localized marketing service isdisclosed herein. The marketing service matches merchant and usersettings including location or proximity and transmits electronicdiscount offers or coupons to matching users (e.g., via SMS . . . ). Theservice can be optimized to maximize utility for one or more of theusers, merchants and the service.

To the accomplishment of the foregoing and related ends, certainillustrative aspects of the claimed subject matter are described hereinin connection with the following description and the annexed drawings.These aspects are indicative of various ways in which the subject mattermay be practiced, all of which are intended to be within the scope ofthe claimed subject matter. Other advantages and novel features maybecome apparent from the following detailed description when consideredin conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a web search system influenced by userlocation.

FIG. 2 is a block diagram of a location filter component.

FIG. 3 is a block diagram of a sensor component.

FIG. 4 is an exemplary screenshot illustrating identification of ageographic region of interest.

FIG. 5 is a block diagram of a web search system influenced by locationand context.

FIG. 6 is a block diagram of a context filter component.

FIG. 7 is a block diagram of a user-context filter component.

FIG. 8 is a block diagram of a personalized web search system thatoperates with respect to designated web content.

FIG. 9 is a block diagram of a personalized web search system includinga generation component for designating web content.

FIG. 10 is a block diagram of a localized marketing system.

FIG. 11 is a block diagram of a localized marketing system including abilling component.

FIG. 12 is a block diagram of a localized marketing system includinginterface and recommendation components.

FIG. 13 is a flow chart diagram of a method of web search.

FIG. 14 is a flow chart diagram of web search methodology.

FIG. 15 is a flow chart diagram of a method of dynamic location basedmarketing.

FIG. 16 is a schematic block diagram illustrating a suitable operatingenvironment for aspects of the subject innovation.

FIG. 17 is a schematic block diagram of a sample-computing environment.

DETAILED DESCRIPTION

The various aspects of the subject innovation are now described withreference to the annexed drawings, wherein like numerals refer to likeor corresponding elements throughout. It should be understood, however,that the drawings and detailed description relating thereto are notintended to limit the claimed subject matter to the particular formdisclosed. Rather, the intention is to cover all modifications,equivalents and alternatives falling within the spirit and scope of theclaimed subject matter.

Given large volumes of information available over the web, there existsa need for mechanisms that restrict content (e.g., web content, queryresults, advertisements . . . ) to that most relevant to a user. Thesubject innovation provides such mechanisms that facilitate filteringcontent based on a bounded location alone or in combination with othercontextual information (e.g., user profile, usage, preferences,tolerance, temporal, third-party, current events . . . ). In thismanner, content can be supplied to a user that is both near andrelevant. Further, note that provided content may vary in real-time asthe bounded region and/or context change.

Referring initially to FIG. 1, a web search system 100 is illustrated inaccordance with an aspect of the subject innovation. The web searchsystem 100 includes a search engine component 110 and a location filtercomponent 120 to enable queries, results, advertisements and the like tobe influenced by location. The search engine component 110 receivesqueries and returns results. Similar to a conventional search engine,component 110 evaluates the received search query to locate relevant webcontent including but not limited to websites, advertisements, blogs,images, audio and video. While the search engine component 110 cansimply be responsive to requests for information via queries, it is alsoto be noted that the search engine component 110 can periodicallyre-execute a query (e.g., predetermined intervals, varying intervals,upon change . . . ) to ensure resulting web content is current andrelevant based on changing circumstances, as will be discussed furtherinfra. Results generated by the re-execution can be provided immediatelyto a user or alternatively cached to facilitate expeditious update.Furthermore, search engine component 110 can update all or portion ofresults at the same or disparate times. For example, relevantadvertisements may be updated more frequently than other identified webcontent. The search engine component 110 is communicatively coupled tothe location filter component 120.

The location filter component 120 facilitates identification of apresent physical location of a user and/or geographical regionassociated with the user's location or simply of interest thereto. Suchlocation data can subsequently be employed to influence web contentreturned with respect to a query, for instance. Web content can be mademore relevant to a user by focusing the content on one or moreparticular regions or locations. For example, if a user generates aquery for “fast food,” results provided for that user's location are themost relevant and useful. The filter component 120 can affect searchresults in one or more of a plethora of disparate manners. In oneinstance, the location filter component 120 can modify a received searchquery to include such location information. Additionally oralternatively, the filter component 120 can filter web content after itis produced as a result of query evaluation. Still further yet, thesearch engine component 110 can be configured to receive locationinformation and automatically filter or influence a query based thereon.

FIG. 2 depicts a location filter component 120 in further detail inaccordance with an aspect of the subject invention. The location filtercomponent 120 includes a determination component 210 that facilitatesidentifying or ascertaining a location and/or bounded region associatedwith or alternatively of interest to a user. Such a determination can bebased on supplied or retrieved information. In one instance, locationinformation can be provided from communicatively coupled sensorcomponent 220. Sensor component 220 supplies or otherwise facilitatessupply of sensed information to determination component 210 that caninterpret the data and identify a location. The determination component220 is also coupled to interface component 230 to enable users toactively specify a location and/or region of interest. The interfacecomponent 230 can correspond to a graphical user interface (GUI) to aidin location identification, among other things.

Further, while a query can be bounded by a predetermined or defaultdistance from an identified location (if not specifically identified),it should also be noted that the distance could be variable based on oneor more factors. For instance, the determination component 210 canutilize a received query, or keywords thereof, to facilitate identifyingan appropriate bounded region. By way of example, if a query pertains tofast food, it is likely that a user wishes to dine somewhere close;thus, the bounded region would be small. By contrast, if a querypertains to vehicles (e.g., cars, boats, motorcycles . . . ), it islikely that a user would travel farther to view and/or purchase such anitem. Accordingly, the search area for vehicles would be much largerthan it was for the fast food query.

FIG. 3 illustrates a sensor component 220 in accordance with an aspectof the subject innovation. As previously mentioned, the sensor component220 can provide the determination component 210 with sensed data to aidin ascertaining a location. In particular, the sensor component 220 caninclude, or in the alternative, be communicatively coupled to globalpositioning system (GPS) sensor 310, wireless sensor 320, radiofrequency identification (RFID) sensor 330, and proximity sensor 340.These sensors can be employed individually or in combination to obtain amore comprehensive view of a user location. The GPS sensor 310 canreceive or retrieve location information from a global positioningsystem based on a device associated with a user (e.g., mobile phone,computer, PDA, pager, watch . . . ). Similarly, wireless sensor 320 canreceive or otherwise obtain data from one or more received ortransmitted wireless signals. For example, data can be received orobtained from one or more wireless signals associated with a user'sphone or other computing device, among other things. Wireless signalinformation can be triangulated to enable identification of anapproximate location. The RFID sensor 330 can receive or retrievelocation data from a radio frequency tag or other like device associatedwith a user. Still further yet, user location can also be sensed baseddata provided by proximity sensor 340. A proximity sensor 340 can detectpresence within an area of the sensor based on an active or passivedevice carried by a user, a facial recognition system, a voicerecognition system or other types of recognition systems.

In addition, sensor component 220 can include an accelerometer sensorcomponent 350 that can receive or retrieve user movement informationfrom an accelerometer or other like device. Along with locationinformation, movement information can be employed to determine orpredict where a user is going and how long it will take them to arrive,inter alia. This enables timely delivery of relevant content to a userbased on current and/or future location. For example, if a user enters aquery for restaurants as he/she is traveling a highway the search regioncan be targeted to restaurants within a short distance from the highwaythat will be approached within a predetermined time given a sensedspeed.

Turning attention to FIG. 4, an exemplary screenshot 400 is illustratedin accordance with an aspect of the subject innovation. As previously,mentioned, a user may desire to specifically identify an area ofinterest. Screenshot 400 depicts a generic map application GUI that canbe employed to identify a particular location via a map 410. While apresent user location can be determined (e.g., via GPS, wireless, IPaddress, RFID . . . ) and identified on the map, as shown at referencenumeral 420, this may or may not be a location of interest to a user ata given time. The subject innovation supports user identification of alocation, region or area of interest in a myriad of different manners.For instance, a user may interact with the map application (e.g., move,zoom in, zoom out . . . ) such that the area displayed corresponds tothe area of interest. Alternatively, a user can identify a particulararea by utilizing an application tool to draw a polygon, circle or otherstandard or non-standard shape around the particular area of interest.Such mechanism can also be employed in combination, to indicate levelsof interest. For example, the area captured by a rectangle at 430 (hereMercer Island) can be the primary and most relevant area of interestwhile the rest of the area displayed can be a secondary area ofinterest. Furthermore, multiple areas can be identified by shapecapture, for example, and include designated priority or relevance data.

FIG. 5 depicts a web search system 500 in accordance with an aspect ofthe innovation. Similar to system 100 of FIG. 1, system 500 includes thesearch engine component 110 and the location filter component 120, aspreviously described. In brief, the search engine component 110 isoperable to receive and satisfy user queries. Resulting web content canbe affected by the location filter component 120 that focuses relevantresults based on one or more particular locations or geographical areas.In addition, system 500 includes context filter component 530communicatively coupled to one or both of the search engine component110 and the location filter component 120. The context filter component530 can further influence the results provided by the search enginecomponent. More specifically, context or information pertaining tostate, setting or circumstances surrounding a query, can be employed toaffect rendered web content. Context information can be provided,determined and/or inferred (as that term is defined herein) and utilizedto improve the relevancy of web content pushed to a user.

FIG. 6 illustrates an exemplary context filter component 530 inaccordance with an aspect of the subject innovation. It should beappreciated the context filter component 530 can include severalsub-components that facilitate receipt, retrieval, determination and/orprediction of specific types of contextual information. Although notlimited thereto, the context filter component 530 can include a usercomponent 610, a temporal component 620, a current events component 630and a third party component 640.

User component 610 pertains to determining information about a userinitiating a query. Such context information enables provided webcontent to be tailored or personalized for each user. By way of exampleand not limitation, resulting web content including identified websitesand advertisements can be tailored to a known or inferred age of theuser. Turning briefly to FIG. 7, an exemplary user component 610 isdepicted in accordance with an aspect of the innovation. As shown thecomponent 610, includes preference component 710, user profile component720, usage analysis component 730 and tolerance component 740.

The preference component 710 provides a mechanism for identifying userpreferences. As with other context information described herein, suchpreferences can be user specified or automatically determined. Forexample, preference information can include the search language, thenumber of results, how results are to be displayed (e.g., presentation,same window, new window . . . ), and type of filters to be applied,among other things. In one instance, a user can specify such preferencesutilizing a graphical user interface (GUI), wizard or the like. If notidentified, default preferences can be employed or the preferences canbe inferred. For instance, if the query is specified in English, then itis likely that the user will want English language content returned.

User profile component 720 obtains or infers particular informationabout a user. Such information can include but is not limited to age,gender, educational level, religion, occupation, ethnicity, likes,dislikes, and political ideology. Again, such information can beemployed to tailor web content to a user. For example, content can becensored for particular age groups such that explicit, sexual, violent,etc. content is not returned to a thirteen-year-old user. In anotherinstance, advanced research papers, doctoral dissertations, and the likecan be filtered such that they are not returned to someone in middleschool or with less than a high school education. It is to beappreciated that user profile or characteristic information can beinferred based on queries, accessed web content, and/or other knowndata, among other things. For instance, if the age of the user can bedetermined within a threshold level of confidence then other things suchas likes, dislikes, and educational level, among other things can beinferred.

Usage analysis component 730 provides a mechanism to influence providedweb content based on past interaction. For example, a user's bookmarks,history, cached content and the like can be utilized to identify pastweb content interaction. Such information can be helpful in identifyinguser characteristics as well as content that may be relevant to a user.For example, bookmarked websites can be noted as trusted web sites suchthat those sites and sites that link to those sites are ranked higher inrelevancy.

Tolerance component 740 assesses a user's cognitive load and/orattention span. Based on the assessment, the amount of web contentpresented to a user can be adjusted. By way of example, if it isdetermined that a user typically only views the first five listedwebsites, then the system can filter the results such that the only fivewebsites are presented. Similarly, while web content such asadvertisements can be continually pushed to a user, advertisements thatare displayed within a time period identified as the user's attentionspan (e.g., first minute) can cost advertisers more than those displayedoutside that span (e.g., prorated based on attention span).

Referring back to FIG. 6, the temporal component 620 can be employed toidentify and filter based on time or time based events. For example, itcan be noted that a holiday such as Valentine's Day is approaching andas a result influence web content based thereon such as byadvertisements for flowers, candy or the like. Of course, the temporalcomponent 620 can be utilized in conjunction with other provided orinferred context information, such that relevant content can be providedfor events personal to a user such as but not limited to birthdays andanniversaries. Furthermore, results can be biased based on past usage atparticular times of varying granularity including but not limited todates, days of the week, and/or time of day.

In addition to regularly occurring events, web content can be basedadditionally or alternatively by current events via current eventscomponent 630. Current events component 630 can monitor nationwideand/or local news wires amongst other outlets such that the informationobtained can be utilized to filter web content provided to a user. Inone exemplary scenario, if a terrorist threat has been identified forsporting arenas across the country and a user searches for a teamwebsite to buy tickets to a game, any content regarding the identifiedterrorist threat can also be provided as highly relevant information.

Third-party component 640 provides a mechanism for filtering contentbased on state/context of one or more people who are not a user. Forinstance, a user can be associated with a group (family, friends,co-workers, professional associations, engaged in a common activity,part of a working collaboration . . . ) and context information relatedto the group and/or individual members can be employed to filter contentprovided to a user. Such information can be obtained from one or morewebsites in one implementation. Furthermore, context associated withgroup members closer in proximity to the user can be deemed morerelevant and thus have more of an effect on provided web content. In oneexemplary implementation, this can be accomplished by comparingcentrally stored location information and group membership, and applyingfilters associated with the group or individuals of the group when theycome within a threshold distance of the user. Alternatively, computingdevices may directly communicate their presence and/or transmitnecessary context information, for instance via infrared or othertransmission media or mechanism.

It is to be noted that the subject innovation is not limited to thecomponents and/or context information identified with respect to FIGS. 6and 7. Various other types of context information can be employed withrespect to the innovation and is to be considered within the scope ofthe appended claims. By way of example and not limitation, contextinformation pertaining to the device a user is employing can beobtained, determined or inferred and utilized to filter and format webcontent. For instance, if the device is a mobile phone, less contentless and/or different content can be displayed to a user. Furthermore,specific context components or portions thereof, described supra, caninteract and/or cooperate to enable specification and identification ofcontext information. For example, knowledge that a user is onlythirteen-years-old can be utilized to infer an education level of lessthan high school. Similarly, the components can interact to facilitateidentification and correction or notification of inconsistent contextinformation.

Turning to FIG. 8, a web search system 800 is shown in accordance withanother aspect of the subject innovation. System 800 includes a searchengine component 110 comprising an interface component 810 and anexecution component 820. The interface component 810 receives, retrievesor otherwise obtains queries and provides results to a requestingentity. Upon receipt of a query, the interface component 810 provides ormakes available the query to execution component 820. The executioncomponent 820 evaluates the query and provides the results to theinterface component 810. More particularly, the execution component 820evaluates the query with respect to at least a subset of web content 830identified by and associated with one or more users. Conventionally, websearch engines evaluate queries with respect to all web content that hasbeen identified by a web crawler. Among other things, the subjectinnovation enables searches to be evaluated with respect to designatedweb content, which may include only a subset of web content. This isbeneficial for a number of reasons. First, queries can be limited tocontent trusted or preferred by a user. Additionally, the designated webcontent can identify content that has not yet been found by a crawler.Thus, system 800 is able to locate content that may not otherwise befound by a conventional search system.

FIG. 9 illustrates a web search system 900 in accordance with an aspectof the innovation. Similar to system 800 of FIG. 8, system 900 caninclude the search engine component 110 including the interfacecomponent 810 and the execution component 820 as well as web content830. As described previously, the interface component 810 can receivequeries provide them to the execution component 820 for evaluation andprovide the results from the execution component 820 back to therequesting entity. Moreover, the results are evaluated with respect toselect web content 830. System 900 also includes a generation component910. Component 910 facilitates generation or identification of selectweb content 830. For example, the generation component may provide agraphical user interface (GUI) or wizard to aid a user in identifyingweb content over which they would like to search. Additionally oralternatively, such content can be inferred from previous interactions,bookmarked favorites and the like. Still further yet, the select webcontent 830 can include or be associated with user ranking informationthat identifies the relevance of content for particular searches to auser. The identified content can then be saved as web content 830. Thesearch engine can then consult web content 830 when evaluating queries.It is also to be appreciated that the generated and saved content 830can be in the form of an index that facilitates expeditious search andlocation of such content.

Referring to FIG. 10, a localized marketing system 1000 is illustratedin accordance with an aspect of the subject innovation. System 1000enables market creation between merchants and potential customers basedon identified criteria as well as location. The system 1000 includes amatch component 1010 that identifies matches between potential customersor system users and merchants. In particular, match component 1010 iscommunicatively coupled to marketing data store 1012 where user andmerchant data is housed and location component 1020 that identifies userlocations, for example based on a broadcast signal from a mobile device.The match component 1010 can search or query the store 1012 to identifyusers and merchants that match desired criteria including location orgeographical proximity. These matches can be provided to component 1030for filtering. The filter component 1030 can identify matches thatmaximize utility, for instance for one or more of a user, merchant andthe marketing system, as will be described further infra. Identifiedmatches are then received or retrieved by the delivery component 1040,which communicates discount offers associated with a matching merchantto associated users. In particular, electronic discount offers can betransmitted to one or more user mobile devices. Delivery component 1040can be a system that actually transmits messages to a user or acomponent that simply constructs messages and provides them to acommunication system such as but not limited to a short message systemfor delivery.

For clarity, consider the following example. Assume that a coffee shopdecides it would like to offer a dollar off coupon to men in theirtwenties that are within a two-block radius of the store. Suppose thatJoe, a system user, is twenty-five years old and has indicated that hewould like to receive special offers from coffee shops within a mileradius. Joe's location can be monitored via any one of a number ofgeo-location systems. For instance, Joe's smart phone can broadcast hislocation to the marketing system 1000 or a system/service associatedtherewith. When Joe is determined to be within a mile of the coffee shopin the subject example nothing happens, since while Joe's conditionshave been satisfied, the coffee shop restrictions have not been met.However, when Joe comes within a two-block radius of the coffee shop, anelectronic discount can be provided to him by the system. Morespecifically, Joe can receive a text message including an alphanumericcode indicating that if Joe presents the code to the coffee shop between5 p.m. and 6 p.m. today, he will receive a dollar off a café latte.

It is to be noted that while Joe may be pushed offers from all merchantsfor which there is a match, the system can engage in filtering, viafilter component 1030, to maximize Joe's utility. For instance, if thereare two coffee shops that match his preferences only the higher valueoffer can be presented (e.g., $2 off coupon over $1 coupon). Likewise,if the discount offers are the same, but one is substantially closer toJoe, then only that offer may be presented.

Alternatively, filtering can be implemented to maximize merchantutility, for instance based on the tightness of a match. For example,the system may transmit a discount offer to a user who is in closerproximity to the store rather than to an individual who is much fartheraway. Furthermore, a merchant may specify a target group or a relevancyhierarchy that can be employed to restrict distribution of offers.

Discount programs can be designed to optimize the likelihood oflong-term revenues by creating patterns of long-term commerce. Forexample, retailers may attempt to incentivize users, who have neverbefore come to a shop, to learn about a shop by sending time-limitedelectronic coupons to attract those users to come for the first time.Such discounts and time deadlines offered with the coupons can be madefunctions of the users' current distances away from the shop and/or someestimate of how far off a user's current path would result by adding awaypoint to the shop. For example, in one approach, the further away auser is, the greater the discount and the more time until the discountexpires.

Such parameters as time until expiration and amount of discount can beoptimized so as to maximize the likelihood that a user will come to ashop for the first time, based on an analysis of the behavior of apopulation of users. Such optimizations can be based on the active studyof responses to multiple combinations of parameters, via a methodicaland automated probe of the behavior of populations with differentdiscounts and deadlines.

Filtering may also be designed to maximize utility associated with themarketing system itself. In one instance, merchants may compete forintroductions to potential customers. For example, merchants within thesame market may offer to pay differing amounts to have their offerspresented to particular types of users. In such a scenario, offersassociated with the highest bidding merchant can be filtered and sent tousers. Further, note that alternative costing schemes can be employed tomaximize revenue for the marketing system.

It is also to be appreciated that filtering can seek to optimize utilityfor more than one party or entity. For example, utility can be maximizedfor two or more of a user, a merchant and the marketing system. Anoptimization algorithm can be employed to determine the best way todistribute merchant discount offers. Alternatively, a greedy algorithmcan be utilized to efficiently identify a solution that approximates anoptimal result.

Further yet, note that while an offer can be pushed to a mobile devicevia SMS or like system, the subject innovation is not so limited. By wayof example and not limitation, an alternate embodiment can be utilizedin conjunction with web search such that electronic offers appear asadvertisements or in another designated portion of a search result page.For instance, if a user issues a search on a mobile device search enginefor fast food, matching electronic offers can be presented together withresults. The innovation has similar utility with respect to alternatetechnologies including but not limited to email and instant messaging.

Referring to FIG. 11, a localized marketing system 1100 is illustratedin accordance with an aspect of the innovation. The marketing system1100 includes the same components as in system 1000 of FIG. 10 with theaddition of a billing component 1110. The billing component 1110 isoperable to automatically generate a bill or invoice, among other thingsfor merchants. The filter component 1030 and the delivery component 1040are communicatively coupled to the billing component 1110. Accordingly,the billing component 1110 can interact with components 1030 and 1040 tofacilitate invoice generation. The actual invoice generated will bedependent upon the economic model adopted by a particular system. Inaccordance, with one aspect of the innovation, merchants can bid on theopportunity to be introduced to specific potential customers. Hence, aprice a merchant pays depends not only on whether it is a winner in thebidding contest, but also on the particular type of potential customerthe bid covers. The billing component 1110 can thus receive anindication of the matching prices for users from filter component 1030.A bill can then be generated upon verification that a merchant's offerhas been sent from delivery component 1040. However, the bill can begenerated solely upon match and an indication thereof from filtercomponent 1030. Furthermore, billing component 1110 can aggregate feesfrom a particular period of time and apply discounts to the bill priorto generation. For example, if a merchant spends a specific amount theymay be entitled to a percentage discount. Furthermore, it is to be notedthat the billing component 1110 can be set up to generate paper orelectronic invoices and/or automatically debit accounts. Further yet,the billing component 1110 is not exclusive to merchants and can thus beutilized in a similar fashion to bill users for service, amongst otherthings.

Turning attention to FIG. 12, a localized marketing system 1200 isdepicted in accordance with an aspect. The system 1200 can include allthe components of system 1100 of FIG. 11, as described above, as well asinterface component 1210 and recommendation component 1220. Theinterface component 1210 provides a mechanism to input marketing datainto store 1012. Among other things, interface component 1210 can be agraphical user interface, such as a web page. Various textual andgraphical objects can facilitate input of constraints to be matched. Forexample, a user may specify that they are interested in coffee,electronics, groceries and entertainment and would like to be notifiedof specials when they are within a two block radius (perhaps becausethey are traveling by foot). Information can also be entered regardinghow users would like to be notified and how location can be determined.Merchants can also utilize interface component 1210 to specify theirdesired matches, offers, bids and billing particulars, inter alia.Accordingly, the interface component 1210 provides a means forautomating inclusion within a marketplace for both merchants and users.

The recommendation component 1220 is a mechanism to aid merchants andusers in specifying useful matching information. The recommendationcomponent 1220 can function together with the interface component 1210to facilitate input of settings. For instance, recommendation component1220 can provide one or more tools or services to maximize merchantbudget utility with respect to specifying matching user demographics,proximities, bids and the like. By way of example, a merchant mayprovide a set budget amount to identify potential customers of interestin a market, and the recommendation component can identify to whomoffers should be presented, for what amount, and how much the merchantshould bid to optimize utility based on the budget. The component 1220can be communicatively coupled to the filter component 1030 and/ormarketing data store 1012 to facilitate analysis of a market includingmatching characteristics and fees charged, amongst other things. Thisinformation can be utilized to recommend certain settings. For instance,if a user indicates that he is interested in video game offers, therecommendation component 1220 can suggest selection of video and/orelectronics categories based on a historical/trend analysis that hasshown these categories produce those types of offers.

The aforementioned systems have been described with respect tointeraction between several components. It should be appreciated thatsuch systems and components can include those components orsub-components specified therein, some of the specified components orsub-components, and/or additional components. For example, contextfilter component 530 can include user component 610, temporal component620, current events component 630 and third party component or anycombination thereof. Sub-components can also be implemented ascomponents communicatively coupled to other components rather thanincluded within parent components. Further yet, one or more componentsand/or sub-components may be combined into a single component providingaggregate functionality. The components may also interact with one ormore other components not specifically described herein for the sake ofbrevity, but known by those of skill in the art.

Furthermore, as will be appreciated, various portions of the disclosedsystems above and methods below may include or consist of artificialintelligence, machine learning, or knowledge or rule based components,sub-components, processes, means, methodologies, or mechanisms (e.g.,support vector machines, neural networks, expert systems, Bayesianbelief networks, fuzzy logic, data fusion engines, classifiers . . . ).Such components, inter alia, can automate certain mechanisms orprocesses performed thereby to make portions of the systems and methodsmore adaptive as well as efficient and intelligent By way of example andnot limitation, such mechanisms can be employed to identify optimizedoffer parameters (e.g., discounts, coupon expiration . . . ) for aparticular objective (e.g., bring in first time shoppers to my retailshop during the next two hours) by performing analysis from datacollected from active probes that link parameters with responses.

By way of example and not limitation, the search engine 110 can cacheand/or immediately display or convey (e.g., audio) web content such asquery results and advertisements based on an inferred or predictedconfidence level that a user would desire or need such information at aparticular point in time (e.g., by employ utility based analysis thatfactors the cost of interruption to the user with the expected benefitto the user of such information). Similarly, cached content can be agedand removed to optimize memory space utilization if such data is nolonger deemed relevant give a new state/context.

In view of the exemplary systems described supra, methodologies that maybe implemented in accordance with the disclosed subject matter will bebetter appreciated with reference to the flow charts of FIGS. 13-15.While for purposes of simplicity of explanation, the methodologies areshown and described as a series of blocks, it is to be understood andappreciated that the claimed subject matter is not limited by the orderof the blocks, as some blocks may occur in different orders and/orconcurrently with other blocks from what is depicted and describedherein. Moreover, not all illustrated blocks may be required toimplement the methodologies described hereinafter. Additionally, itshould be further appreciated that the methodologies disclosedhereinafter and throughout this specification are capable of beingstored on an article of manufacture to facilitate transporting andtransferring such methodologies to computers.

Referring to FIG. 13, a web search method 1300 is depicted in accordancewith an aspect of the subject innovation. At reference numeral 1310, aweb query is received. At numeral 1320, location information isreceived. This information can be associated with a physical location ofan entity providing the query or simply an area of interest. Forexample, sensors can receive or retrieve data corresponding to thelocation of a user (e.g., via GPS, wireless, RFID . . . ) oralternatively, a user can select an area of interest from a map, amongother things. At reference numeral 1330, context information is receivedor otherwise obtained. Context information can pertain to anycircumstances surrounding the query including but not limited to usercontext (e.g., profile, characteristics, preferences, previous use,attention span, group membership . . . ) temporal context (e.g., season,date, time of day, day of week . . . ), current event context (e.g.,local, national, familial or associated group news . . . ) and/or thirdparty context (e.g., state/context of non-user in an associated group,engaged in common activity, part of a working collaboration . . . ). Atnumeral 1340, the received query is evaluated and constrained orfiltered with respect to one or both of location and context. At 1350,the resulting content is returned to a requesting entity, for instanceto display to a user. As previously mentioned, it is to be noted thatthe subject method 1300 can be executed manually when a query isreceived and/or automatically to enable content to be pushed to a userat various times.

As an example, consider a scenario where a user traveling by bus anddesiring to eat enters a query for fast food restaurants. After theuser's query is received, the user's location can be identified.Furthermore, based on the starting and stopping detected by anaccelerometer it can be inferred that a user is on a bus. Therefore, thesearch location can be limited to a known or inferred bus route. Contextcan also be evaluated and employed to further aid in identifyingrelevant content. For instance, if it is known or can be inferred thatthe user is Catholic and it is Lent, this information can be employed tofurther filter relevant fast food restaurants based on the extent oftheir non-meat menu and user likes and/or dislikes. As a result, theentered fast food query be evaluated and filtered such that the mostrelevant web content will pertain to restaurants closest to the busroute, which have the best non-meat menu given the users likes anddislikes.

FIG. 14 illustrates a web search methodology 1400 according to anotheraspect of the innovation. At reference numeral 1410, a web query isreceived. At 1420, web content associated with a user is identified. Forexample, a user can identify at least a subset of web content over whichqueries are to be evaluated utilizing a GUI or wizard to facilitateinput. The identified subset can allow a user to receive results theylikely desire, among other things. Furthermore, the select web contentcan in some instances identify content that has not been indexed (ifever) by an engine crawler and therefore is unavailable for queryevaluation. Therefore, searches are not bound to what crawlers find. Atreference numeral 1430, the received query is evaluated with respect tothe identified content. The results are then conveyed to a requestingentity at numeral 1440.

Referring to FIG. 15, a dynamic location based marketing method 1500 isdepicted in accordance with an aspect of the subject innovation. Method1500 can be employed as a service to provide matching merchant discountsto users or service subscribers. At reference numeral 1510, merchantsettings can be received. These settings can include user demographicsincluding proximity, offers and bids for introductions, among otherthings. User settings are received at 1520. These settings can includespecification of merchants or classes or categories of merchants fromwhich a user would be interested in receiving offers. Additionalinformation can also be set including a proximity or location, method ofnotification, and location tracking information, among other things.Both merchant and user settings can be stored for further processing. Atnumeral 1530, user locations are identified. For example, a serviceassociated with user mobile devices can be contacted to receivegeolocation information. Additionally or alternatively, various othermeans of location can be utilized including proximity sensors topinpoint user locations. One or more merchants and users are matched at1540. Matching can be done based on settings and current user locations.At reference numeral 1550, matches are then filtered, for instance tooptimize utility of one or more of user(s), merchant(s) and themarketing system. Discount offers can be sent, at 1560, to user devices.In one embodiment, the discount offer can be an electronic couponincluding one or more alphanumeric characters that can be provided to aspecific merchant to redeem the value thereof. The method 1500 cansubsequently terminate. However, it is to be appreciated that the method1500 likely loop continuously to update, match and filter based onmerchant and user settings as well as location. Note that a match maynot occur because a user is outside a set distance of a merchant,however, seconds later he/she may be within the boundary and thus amatch would occur on the next method loop or iteration.

As used herein, the terms “component” and “system” and the like areintended to refer to a computer-related entity, either hardware, acombination of hardware and software, software, or software inexecution. For example, a component may be, but is not limited to being,a process running on a processor, a processor, an object, an instance,an executable, a thread of execution, a program and/or a computer. Byway of illustration, both an application running on a computer and thecomputer can be a component. One or more components may reside within aprocess and/or thread of execution and a component may be localized onone computer and/or distributed between two or more computers.

The word “exemplary” is used herein to mean serving as an example,instance, or illustration. Any aspect or design described herein as“exemplary” is not necessarily to be construed as preferred oradvantageous over other aspects or designs. Similarly, examples areprovided herein solely for purposes of clarity and understanding and arenot meant to limit the subject innovation or portion thereof in anymanner. It is to be appreciated that a myriad of additional or alternateexamples could have been presented, but have been omitted for purposesof brevity.

Machine learning and reasoning systems (e.g., explicitly and/orimplicitly trained classifiers) can be employed in connection withperforming inference and/or probabilistic determinations and/orstatistical-based determinations as in accordance with one or moreaspects of the subject innovation as described hereinafter. As usedherein, the term “inference” or “infer” refers generally to the processof reasoning about or inferring states of the system, environment,and/or user from a set of observations as captured via events and/ordata. Inference can be employed to identify a specific context oraction, or can generate a probability distribution over states, forexample. The inference can be probabilistic—that is, the computation ofa probability distribution over states of interest based on aconsideration of data and events. Inference can also refer to techniquesemployed for composing higher-level events from a set of events and/ordata. Such inference results in the construction of new events oractions from a set of observed events and/or stored event data, whetheror not the events are correlated in close temporal proximity, andwhether the events and data come from one or several event and datasources. Various classification schemes and/or systems (e.g., supportvector machines, neural networks, expert systems, Bayesian beliefnetworks, fuzzy logic, data fusion engines . . . ) can be employed inconnection with performing automatic and/or inferred action inconnection with the subject innovation.

Furthermore, all or portions of the subject innovation may beimplemented as a method, apparatus, or article of manufacture usingstandard programming and/or engineering techniques to produce software,firmware, hardware or any combination thereof to control a computer toimplement the disclosed innovation. The term “article of manufacture” asused herein is intended to encompass a computer program accessible fromany computer-readable device or media. For example, computer readablemedia can include but are not limited to magnetic storage devices (e.g.,hard disk, floppy disk, magnetic strips . . . ), optical disks (e.g.,compact disk (CD), digital versatile disk (DVD) . . . ), smart cards andflash memory devices (e.g., card, stick, jump drive . . . ).Additionally, it should be appreciated that a carrier wave can beemployed to carry computer-readable electronic data such as those usedin transmitting and receiving electronic mail or in accessing a networksuch as the Internet or a local area network (LAN). Of course, thoseskilled in the art will recognize many modifications may be made to thisconfiguration without departing from the scope or spirit of the claimedsubject matter.

In order to provide a context for the various aspects of the disclosedsubject matter, FIGS. 16 and 17 as well as the following discussion areintended to provide a brief, general description of a suitableenvironment in which the various aspects of the disclosed subject mattermay be implemented. While the subject matter has been described above inthe general context of computer-executable instructions of a computerprogram that runs on a computer and/or computers, those skilled in theart will recognize that the subject innovation also may be implementedin combination with other program modules. Generally, program modulesinclude routines, programs, components, data structures, etc. thatperform particular tasks and/or implement particular abstract datatypes. Moreover, those skilled in the art will appreciate that theinventive methods may be practiced with other computer systemconfigurations, including single-processor or multiprocessor computersystems, mini-computing devices, mainframe computers, as well aspersonal computers, hand-held computing devices (e.g. personal digitalassistant (PDA), phone, watch . . . ), microprocessor-based orprogrammable consumer or industrial electronics, and the like. Theillustrated aspects may also be practiced in distributed computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. However, some, if not allaspects of the claimed innovation can be practiced on stand-alonecomputers. In a distributed computing environment, program modules maybe located in both local and remote memory storage devices.

With reference to FIG. 16, an exemplary environment 1610 forimplementing various aspects disclosed herein includes a computer 1612(e.g., desktop, laptop, server, hand held, programmable consumer orindustrial electronics . . . ). The computer 1612 includes a processingunit 1614, a system memory 1616, and a system bus 1618. The system bus1618 couples system components including, but not limited to, the systemmemory 1616 to the processing unit 1614. The processing unit 1614 can beany of various available microprocessors. Dual microprocessors and othermultiprocessor architectures (e.g., multi-core) also can be employed asthe processing unit 1614.

The system bus 1618 can be any of several types of bus structure(s)including the memory bus or memory controller, a peripheral bus orexternal bus, and/or a local bus using any variety of available busarchitectures including, but not limited to, 11-bit bus, IndustrialStandard Architecture (ISA), Micro-Channel Architecture (MSA), ExtendedISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Universal Serial Bus (USB),Advanced Graphics Port (AGP), Personal Computer Memory CardInternational Association bus (PCMCIA), and Small Computer SystemsInterface (SCSI).

The system memory 1616 includes volatile memory 1620 and nonvolatilememory 1622. The basic input/output system (BIOS), containing the basicroutines to transfer information between elements within the computer1612, such as during start-up, is stored in nonvolatile memory 1622. Byway of illustration, and not limitation, nonvolatile memory 1622 caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable ROM (EEPROM), or flashmemory. Volatile memory 1620 includes random access memory (RAM), whichacts as external cache memory.

Computer 1612 also includes removable/non-removable,volatile/non-volatile computer storage media. FIG. 16 illustrates, forexample, mass or auxiliary storage 1624. Mass storage 1624 includes, butis not limited to, devices like a magnetic disk drive, floppy diskdrive, tape drive, Jaz drive, Zip drive, LS-100 drive, flash memorycard, or memory stick. In addition, mass storage 1624 can includestorage media separately or in combination with other storage mediaincluding, but not limited to, an optical disk drive such as a compactdisk ROM device (CD-ROM), CD recordable drive (CD-R Drive), CDrewritable drive (CD-RW Drive) or a digital versatile disk ROM drive(DVD-ROM). To facilitate connection of the mass storage devices 1624 tothe system bus 1618, a removable or non-removable interface is typicallyused such as interface 1626.

It is to be appreciated that FIG. 16 describes software that acts as anintermediary between users and the basic computer resources described insuitable operating environment 1610. Such software includes an operatingsystem 1628. Operating system 1628, which can be stored on mass storage1624 and loaded to system memory 1616, acts to control and allocateresources of the system 1612. System applications 1630 take advantage ofthe management of resources by operating system 1628 through programmodules 1632 and program data 1634 stored either in system memory 1616or on mass storage 1624. It is to be appreciated that the subjectinnovation can be implemented with various operating systems orcombinations of operating systems.

A user enters commands or information into the computer 1612 throughinput device(s) 1636. Input devices 1636 include, but are not limitedto, a pointing device such as a mouse, trackball, stylus, touch pad,keyboard, microphone, joystick, game pad, satellite dish, scanner, TVtuner card, digital camera, digital video camera, web camera, and thelike. These and other input devices connect to the processing unit 1614through the system bus 1618 via interface port(s) 1638. Interfaceport(s) 1638 include, for example, a serial port, a parallel port, agame port, and a universal serial bus (USB). Output device(s) 1640 usesome of the same type of ports as input device(s) 1636. Thus, forexample, a USB port may be used to provide input to computer 1612 and tooutput information from computer 1612 to an output device 1640. Outputadapter 1642 is provided to illustrate that there are some outputdevices 1640 like displays (e.g., flat panel, CRT, LCD, plasma . . . ),speakers, and printers, among other output devices 1640 that requirespecial adapters. The output adapters 1642 include, by way ofillustration and not limitation, video and sound cards that provide ameans of connection between the output device 1640 and the system bus1618. It should be noted that other devices and/or systems of devicesprovide both input and output capabilities such as remote computer(s)1644.

Computer 1612 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1644. The remote computer(s) 1644 can be a personal computer, a server,a router, a network PC, a workstation, a microprocessor based appliance,a peer device or other common network node and the like, and typicallyincludes many or all of the elements described relative to computer1612. For purposes of brevity, only a memory storage device 1646 isillustrated with remote computer(s) 1644. Remote computer(s) 1644 islogically connected to computer 1612 through a network interface 1648and then physically connected (e.g., wired or wirelessly) viacommunication connection 1650. Network interface 1648 encompassescommunication networks such as local-area networks (LAN) and wide-areanetworks (WAN).

Communication connection(s) 1650 refers to the hardware/softwareemployed to connect the network interface 1648 to the bus 1618. Whilecommunication connection 1650 is shown for illustrative clarity insidecomputer 1612, it can also be external to computer 1612. Thehardware/software necessary for connection to the network interface 1648includes, for exemplary purposes only, internal and externaltechnologies such as, modems including regular telephone grade modems,cable modems, power modems and DSL modems, ISDN adapters, and Ethernetcards or components.

FIG. 17 is a schematic block diagram of a sample-computing environment1700 with which the subject innovation can interact. The system 1700includes one or more client(s) 1710. The client(s) 1710 can be hardwareand/or software (e.g., threads, processes, computing devices). Thesystem 1700 also includes one or more server(s) 1730. Thus, system 1700can correspond to a two-tier client server model or a multi-tier model(e.g., client, middle tier server, data server), amongst other models.The server(s) 1730 can also be hardware and/or software (e.g., threads,processes, computing devices). The servers 1730 can house threads toperform transformations by employing the subject innovation, forexample. One possible communication between a client 1710 and a server1730 may be in the form of a data packet transmitted between two or morecomputer processes.

The system 1700 includes a communication framework 1750 that can beemployed to facilitate communications between the client(s) 1710 and theserver(s) 1730. The client(s) 1710 are operatively connected to one ormore client data store(s) 1760 that can be employed to store informationlocal to the client(s) 1710. Similarly, the server(s) 1730 areoperatively connected to one or more server data store(s) 1740 that canbe employed to store information local to the servers 1730.

What has been described above includes examples of aspects of theclaimed subject matter. It is, of course, not possible to describe everyconceivable combination of components or methodologies for purposes ofdescribing the claimed subject matter, but one of ordinary skill in theart may recognize that many further combinations and permutations of thedisclosed subject matter are possible. Accordingly, the disclosedsubject matter is intended to embrace all such alterations,modifications and variations that fall within the spirit and scope ofthe appended claims. Furthermore, to the extent that the terms“includes,” “has” or “having” or variations in form thereof are used ineither the detailed description or the claims, such terms are intendedto be inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim.

What is claimed is:
 1. A system for web searching, comprising; aprocessor; a memory communicatively coupled to the processor, the memoryhaving stored therein computer-executable instructions configured toimplement the web search system including: a search component thatidentifies relevant web content in accordance with a query from a user;a location component that identifies limited web content by limiting therelevant web content to a geographic region surrounding a presentphysical location of the user, the user associated with a group of oneor more people, the group comprising family of the user, friends of theuser, co-workers of the user, people engaged in a common activity withthe user or people engaged in a working collaboration with the user; acontext component that filters the limited web content based on userinformation and context information corresponding to one or more membersof the group who are not the user, the context information beingobtained, for each of the one or more members, via a computing device ofa respective member of the one or more members; and an interfacecomponent that presents the filtered, limited web content to the user,wherein: the location component includes a determination component thatautomatically identifies the location of a user based on data providedby one or more sensors, the one or more sensors providing one or more ofGPS, Wi-Fi, RFID, proximity or acceleration data; and a size of thegeographic region is determined based at least in part on theacceleration data, wherein the acceleration data includes a rate atwhich the location of the user changes.
 2. The system of claim 1, thelocation component includes a determination component that identifiesthe geographic region based on information specified by the user.
 3. Thesystem of claim 1, the location component includes a determinationcomponent that determines a boundary of the geographic region based atleast in part on a keyword in the query.
 4. The system of claim 1, theuser information identifies characteristics of the user including atleast one of age, gender, ethnicity, education level or politicalaffinity.
 5. The system of claim 1, the user information includesmaximum cognitive load or attention span that is employed to limit theamount of content provided at one time.
 6. The system of claim 1, userinformation includes one of previous searches and selected content. 7.The system of claim 1, the context component filters the limited webcontent based on one of current events and temporal data.
 8. The systemof claim 1, the search component pushes advertisements that are near andrelevant to a particular user based at least in part on the geographicregion and the user information, the pushed advertisements optimized tomaximize utility for at least one of the particular user or a merchant.9. A method comprising: employing a processor executing computerexecutable instructions stored on a computer readable storage medium toimplement the following acts: identifying a present physical location ofa user as an identified location; monitoring news wires to identifycurrent events; receiving a web search query that includes one or morekeywords, wherein none of the one or more keywords represents theidentified current events; filtering the web search query using criteriabased on: a region including the identified location, the identifiedcurrent events, and user information; returning web search results thatinclude information associated with the identified current events basedat least in part on the filtering; adjusting boundaries of the region inthe web search results based on at least one keyword in the web searchquery; limiting the search query or sources of content based oninformation about the user and group context information associated witha group, the user associated with the group, the group contextinformation corresponding to one or more members of the group who arenot the user; and limiting the search query or sources of content suchthat group context information of a member of the group who isphysically closer to the user has a greater effect on limiting resultsof the search query than does group context information of a member ofthe group who is physically further from the user.
 10. The method ofclaim 9, wherein the user information includes one or more of user age,gender, education, ethnicity, religion, or political affiliation. 11.The method of claim 9, the acts further comprising filtering the websearch queries based on historical click through.
 12. The method ofclaim 9, further comprising filtering advertisements displayed withsearch results based on one or more of the identified location or userinformation.
 13. The method of claim 9, further comprising receiving auser-selected portion of a map that specifies the identified location.14. The method of claim 9, further comprising determining the identifiedlocation from the present geographical position of the user.
 15. Themethod of claim 9, further comprising limiting the number of resultsreturned based on user tolerance.
 16. The method of claim 9, furthercomprising filtering search queries based on context.
 17. The method ofclaim 9, wherein: adjusting boundaries of the region in the web searchresults based on at least one keyword in the web search query comprisesadjusting boundaries of the region based on a location of an item towhich a query pertains, the item being identified based on the at leastone keyword.
 18. A system, embodied on a computer readable storagemedium, that when executed by a processor, facilitates web-basedsearching, comprising: means for identifying a present location of auser; means for predicting a future location of the user based at leastin part on acceleration data; first means for limiting at least one ofsearch queries or sources of content based on the predicted futurelocation; and second means for limiting the at least one of searchqueries or sources of content based on information about the user andgroup context information associated with a group, the user associatedwith the group, the group context information corresponding to one ormore members of the group who are not the user, wherein the second meansfor limiting limits the at least one of search queries or sources ofcontent such that group context information of a member of the group whois physically closer to the user has a greater effect on limitingresults of the at least one search query than does group contextinformation of a member of the group who is physically further from theuser.
 19. A system comprising: a processor; a memory communicativelycoupled to the processor, the memory having stored thereincomputer-executable instructions configured to implement the web searchsystem including: a search component that identifies relevant webcontent in accordance with a query; a location component that identifieslimited web content by limiting the relevant web content to a regionsurrounding a present physical location of a user, wherein: the regionis not specifically included in the query; the region comprisesdimensions based at least in part on a dimension associated with akeyword of the query; and the dimension is not entered by the user; anda context component that filters the limited web content based on userinformation; and a third-party component that obtains contextinformation associated with at least one of a group or individualmembers of the group, wherein: the group comprises a plurality ofindividual members; and the context component filters the limitedcontent using criteria based on the context information associated withthe at least one of the group or individual members of the group suchthat the context information associated with a member of the group whois physically closer to the user has a greater effect on limitingresults of the query than does context information associated with amember of the group who is physically further from the user.
 20. Thesystem of claim 1, wherein the group is a group of friends of the user,and the context information corresponding to one or more members of thegroup comprises a location of a member of the group.